Generating legal research recommendations from an input data source

Abstract

Embodiments of the present disclosure support systems and methods providing functionality for identifying legal authorities from input data that does not contain legal citations. The legal authorities may be identified by first extracting a set of features from input data. The set of features may be used to identify a set of candidate legal authorities. The set of candidate legal authorities may be ranked and/or pruned to produce a set of legal authorities that are highly relevant to legal issues and facts within the input data.

What is claimed is: 
     
         1 . A system comprising,
 a memory; and   one or more processors coupled to the memory, the one or more processors configured to perform steps, comprising:
 extracting, by the one or more processors, a set of data segments from input data, wherein the input data comprises information associated with one or more legal issues and does not contain citations to legal authorities; 
 identifying, by the one or more processors, a set of features in the set of data segments extracted from the input data, the set of features corresponding to the one or more legal issues and related to one or more points of law, a set of facts, or a combination thereof; 
 determining, by the one or more processors, a set of candidate legal authorities based on the set of features, wherein the set of candidate legal authorities are determined based on a query of a data source based on the set of features, and wherein the set of candidate legal authorities comprise legal documents; 
 pruning, by the one or more processors, the set of candidate legal authorities to generate a reduced set of candidate legal authorities; and 
 outputting, by the one or more processors, a ranked set of legal authorities based on the reduced set of candidate legal authorities. 
   
     
     
         2 . The system of  claim 1 , further comprising converting the input data to a machine readable format via natural language processing prior to extracting the set of data segments. 
     
     
         3 . The system of  claim 1 , wherein the input data comprises jurisdiction information designating one or more jurisdictions of interest, and wherein the extracting is based at least in part on the one or more jurisdictions of interest, wherein the set of candidate authorities are associated with the one or more jurisdictions of interest, and wherein the set of candidate authorities correspond to a treatment of the one or more legal issues within the one or more jurisdictions of interest. 
     
     
         4 . The system of  claim 1 , wherein the extracting comprises determining section boundaries and headings from the input data, and wherein the input data comprises an email, a letter, a pleading, a court filing, a brief, an article, a memo, a draft version of one of the preceding types of input data, or a combination thereof. 
     
     
         5 . The system of  claim 1 , wherein pruning the set of candidate legal authorities comprises filtering the set of candidate legal authorities based on at least one Westlaw® Key Number corresponding to the one or more points of law. 
     
     
         6 . The system of  claim 1 , further comprising, prior to the pruning:
 identifying keywords within the set of data segments; and   ranking the set of set of candidate authorities based at least in part on the keywords.   
     
     
         7 . The system of  claim 1 , further comprising applying a neural language model to the input data, the neural language model configured to prioritize candidate legal authorities from the set of candidate legal authorities corresponding to the one or more points of law. 
     
     
         8 . A method, comprising:
 extracting, by the one or more processors, a set of data segments from input data, wherein the input data comprises information associated with one or more legal issues and does not contain citations to legal authorities;   identifying, by the one or more processors, a set of features in the set of data segments extracted from the input data, the set of features corresponding to the one or more legal issues and related to one or more points of law, a set of facts, or a combination thereof;   determining, by the one or more processors, a set of candidate legal authorities based on the set of features, wherein the set of candidate legal authorities are determined based on a query of a data source based on the set of features, and wherein the set of candidate legal authorities comprise legal documents;   pruning, by the one or more processors, the set of candidate legal authorities to generate a reduced set of candidate legal authorities; and   outputting, by the one or more processors, a ranked set of legal authorities based on the reduced set of candidate legal authorities.   
     
     
         9 . The method of  claim 8 , further comprising converting the input data to a machine readable format via natural language processing prior to extracting the set of data segments. 
     
     
         10 . The method of  claim 8 , wherein the input data comprises jurisdiction information designating one or more jurisdictions of interest, and wherein the extracting is based at least in part on the one or more jurisdictions of interest, wherein the set of candidate authorities are associated with the one or more jurisdictions of interest, and wherein the set of candidate authorities correspond to a treatment of the one or more legal issues within the one or more jurisdictions of interest. 
     
     
         11 . The method of  claim 8 , wherein the extracting comprises determining section boundaries and headings from the input data, and wherein the input data comprises an email, a letter, a pleading, a court filing, a brief, an article, a memo, a draft version of one of the preceding types of input data, or a combination thereof. 
     
     
         12 . The method of  claim 8 , wherein pruning the set of candidate legal authorities comprises filtering the set of candidate legal authorities based on at least one Westlaw® Key Number corresponding to the one or more points of law. 
     
     
         13 . The method of  claim 8 , further comprising, prior to the pruning:
 identifying keywords within the set of data segments; and   ranking the set of set of candidate authorities based at least in part on the keywords.   
     
     
         14 . The method of  claim 8 , further comprising applying a neural language model to the input data, the neural language model configured to prioritize candidate legal authorities from the set of candidate legal authorities corresponding to the one or more points of law over candidate legal authorities corresponding to the set of facts. 
     
     
         15 . A computer program product, comprising:
 a non-transitory computer readable medium comprising code for performing steps comprising:
 extracting, by the one or more processors, a set of data segments from input data, wherein the input data comprises information associated with one or more legal issues and does not contain citations to legal authorities; 
 identifying, by the one or more processors, a set of features in the set of data segments extracted from the input data, the set of features corresponding to the one or more legal issues and related to one or more points of law, a set of facts, or a combination thereof; 
 determining, by the one or more processors, a set of candidate legal authorities based on the set of features, wherein the set of candidate legal authorities are determined based on a query of a data source based on the set of features, and wherein the set of candidate legal authorities comprise legal documents; 
 pruning, by the one or more processors, the set of candidate legal authorities to generate a reduced set of candidate legal authorities; and 
 outputting, by the one or more processors, a ranked set of legal authorities based on the reduced set of candidate legal authorities. 
   
     
     
         16 . The computer program product of  claim 15 , further comprising converting the input data to a machine readable format via natural language processing prior to extracting the set of data segments. 
     
     
         17 . The computer program product of  claim 15 , wherein the input data comprises jurisdiction information designating one or more jurisdictions of interest, and wherein the extracting is based at least in part on the one or more jurisdictions of interest, wherein the set of candidate authorities are associated with the one or more jurisdictions of interest, and wherein the set of candidate authorities correspond to a treatment of the one or more legal issues within the one or more jurisdictions of interest. 
     
     
         18 . The computer program product of  claim 15 , wherein the extracting comprises determining section boundaries and headings from the input data, and wherein the input data comprises an convert. 
     
     
         19 . The computer program product of  claim 15 , wherein pruning the set of candidate legal authorities comprises filtering the set of candidate legal authorities based on at least one Westlaw® Key Number corresponding to the one or more points of law. 
     
     
         20 . The computer program product of  claim 15 , further comprising, prior to the pruning:
 identifying keywords within the set of data segments; and   ranking the set of set of candidate authorities based at least in part on the keywords.